Exercise 1_4_1: Basic Raster Operations

1

Create a matrix with 8 rows and 8 columns filles with random numbers in a range between 1 and 1000.

Clues

You can use the sample() function to create the numbers.

solution

library(dplyr)

fancy_matrix <-
  sample(1:1000, 8*8, replace = TRUE) %>% 
  matrix(nrow = 8, ncol = 8)

fancy_matrix

##      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
## [1,]  731  896  825  343  633  303  850  674
## [2,]  891  602  970  399  369  362  406  219
## [3,]  210  348  750   47  973  400   95  699
## [4,]  207  225  136   15  589  351   57  682
## [5,]  642  767  927  102  140   52  628   66
## [6,]  587  550  886  316  421   70  848  208
## [7,]  447  492  222  428  311  803  834  863
## [8,]  600  388  197  506   32  716  697  966

2

Now use this matrix to create a raster layer and plot it.

Clues

The terra::rast() function can be fed with matrices to create a raster layer.

solution

library(terra)

fancy_raster_layer <-
  terra::rast(fancy_matrix)

terra::plot(fancy_raster_layer)

The raster() function can not only be used to create raster data on the fly, which is also not very interesting. Instead, we can use it to import already prepared data.

3

Import one of the raster .tiff files in the ./data/ folder of the workshop directory (repository).

Clues

Make sure your file paths are set correctly. You can check them with getwd(). Setting is done with setwd().

solution

immigrants_cologne <-
  terra::rast("./data/immigrants_cologne.tif")

4

Import the data on Immigrants, Germans, and Inhabitants. Add up the Immigrants and Germans to a new layer. Then subtract this new layer from the Inhabitants layer to check whether the inhabitant layer is the same as the sum of immigrants and Germans. Is it?

Clues

You can handle raster layers as any simple data table using + and - operators.

solution

# load all layers
immigrants_cologne <-
  terra::rast("./data/immigrants_cologne.tif")

germans_cologne <-
  terra::rast("./data/germans_cologne.tif")

inhabitants_cologne <-
  terra::rast("./data/inhabitants_cologne.tif")

# create sum layer
immigrants_germans_sum <-
  immigrants_cologne + germans_cologne

# create difference layer
difference_layer <-
  inhabitants_cologne - immigrants_germans_sum

difference_layer

## class       : SpatRaster 
## dimensions  : 289, 264, 1  (nrow, ncol, nlyr)
## resolution  : 100, 100  (x, y)
## extent      : 4094850, 4121250, 3084050, 3112950  (xmin, xmax, ymin, ymax)
## coord. ref. : ETRS89-extended / LAEA Europe (with axis order normalized for visualization) 
## source      : memory 
## name        : inhabitants_cologne 
## min value   :                  -2 
## max value   :                   0

# get a summary statistic
summary(difference_layer)

##     Length      Class       Mode 
##          1 SpatRaster         S4

# create a table of counts
difference_layer %>% 
  as.data.frame() %>% 
  table()

## inhabitants_cologne
##    -2    -1     0 
##    11  2052 11711